There may not exist a regressor that can properly fit the data for all the surveys, similar to the no-free-lunch theorem (a machine-learning algorithm that can solve every problem does not exist; [1]}). This implies that the prediction would be biased, if we use single catalog or priority-based methods to regress the data in another catalog. In machine learning, a larger amount of data does not always work, but higher diversity does [2]}.
